Advancements in modern computing have led to an increased use of visual computing for a variety of mainstream computing applications. In particular, rapid deployments of cameras have been leveraged for numerous visual computing applications that rely on large-scale video analytics and visual data processing. Existing approaches to large-scale visual computing, however, suffer from numerous limitations. For example, existing visual computing approaches are implemented using rigid designs that utilize resources inefficiently and provide limited functionality, privacy, and security. As a result, existing approaches often suffer from high latency and are inaccurate, unreliable, inflexible, and incapable of scaling efficiently.